Which term describes a sample that includes random selection from a defined population?

A sample that includes random selection from a defined population is best described as a simple random sample. In a simple random sample, every individual in the population has an equal chance of being chosen for the sample. This method ensures that the sample is representative of the overall population, which is crucial for the validity of statistical analysis.

The hallmark of simple random sampling is its straightforward approach, where selection can be achieved using random mechanisms such as random number generators, drawing lots, or other techniques that do not introduce bias. This characteristic is vital in research and experimental design, as it allows for generalizations to be made about the population based on the sample data.

In contrast, other sampling methods like stratified sampling involve dividing the population into distinct subgroups before random selection, which may not provide the same level of overall randomness. Cluster sampling groups the population into clusters and then randomly selects entire clusters rather than individuals, while systematic sampling involves selecting samples at regular intervals, which might introduce a pattern or bias. Thus, simple random sampling stands out as the method that encapsulates the essence of random selection from a defined population.